Algorithms for automatic extraction of feature values of corneal endothelial cells using genetic programming
Tomoyuki Hiroyasu, Sakito Nunokawa, Hiroaki Yamaguchi, Noriko Koizumi, Naoki Okumura, Hisatake Yokouchi · 2012
In cornea tissue engineering, a researcher measures cell density and a form, in order to check the status of a cultivated cell. In this paper, these features values of cells are extracted automatically from corneal endothelial cell images. In the proposed method, genetic programing (GP) is used to construct image filters which can detect cell regions from corneal endothelial cells images. After detecting cell regions, feature values of cells such as density, the number of hexagon cells, and cell sizes are derived. To discuss the effectiveness of the proposed algorithm, the algorithm is applied to 16 sheets of corneal endothelial cells images. The cell region detection process was compared with the results of the Watershed filter which is one of the existing region division filters. From the results, it is confirmed that the filters which can extract cell regions from eight sheets of images with low error compared with the Watershed filter were constructed by GP. At the same time, it is also confirmed that the feature values of cells are detected successfully from five sheets of images.